How would you prefer to be sliced and diced?
Analytics has been pushed to the foreground of American minds by the 2008 election cycle. TV and news media provide seemingly endless hours of pundits and commentators discussing data and predictions. This analysis is based off of complex modeling as well as basic segmentation; political analytics brought us the terms "Soccer Moms" and "NASCAR dads" after all. While not the professional specialty area of most that read this blog, analytics is getting a lot of attention, and in many cases being applied in increasingly prominent ways.
I recently finished the book Microtrends by Political Analyst Svengali Mark Penn. The book offers a provocative analysis of “undiscovered,” yet potentially important populations in America, and promoted strategies on how to engage them and effect change. This idea of almost hyper segmentation has forced me to consider the ways in which I segment data and the resulting application.
I fundamentally believe that studying a heterogeneous group on a more micro level has great benefits, but I believe there can be costs as well. I hope others in our field give thoughtful consideration to the ways we “slice and dice” our data, as well as how “fine” we choose too cut.
You can segment individuals in a variety of ways, but many of these ways may not be useful for the questions you seek to answer. I may be identified as a “mid-twenties jazz music buff,” an “urban chess student and wine lover,” or as someone who “drives American” because I own a Pontiac. These are all accurate segments that connect me with others and offer some snapshots into my interests and purchasing preferences—but is it helpful to you? I feel there is a normal distribution related to the amount of segmentation conducted—a natural sweet spot, after which further division can create more problems than answers, or more incorrect conclusions than accurate ones.
Following the questions of “how do we cut” as well as “how deep” lies the next step: how should we use this information? Does segmentation serve as the sign post for a new fundraising strategy? Or does it simply signal more research? There are successful applications of both I believe, but it depends on the segmentation process and the questions you are trying to answer.
Read this article, consider analytic's emerging seat at the table in our world, and then ask yourself this question:
“How would I want to be identified (segmented) by organizations or causes I care about?”
What’s for Dinner? The pollsters want to know
If there’s butter and white wine in your refrigerator and Fig Newtons in the cookie jar, you’re likely to vote for Hillary Clinton. Prefer olive oil, Bear Naked granola and a latte to go? You probably like Barack Obama, too. And if you’re leaning toward John McCain, it’s all about kicking back with a bourbon and a stuffed crust pizza while you watch the Democrats fight it out next week in Pennsylvania.
Read More
I recently finished the book Microtrends by Political Analyst Svengali Mark Penn. The book offers a provocative analysis of “undiscovered,” yet potentially important populations in America, and promoted strategies on how to engage them and effect change. This idea of almost hyper segmentation has forced me to consider the ways in which I segment data and the resulting application.
I fundamentally believe that studying a heterogeneous group on a more micro level has great benefits, but I believe there can be costs as well. I hope others in our field give thoughtful consideration to the ways we “slice and dice” our data, as well as how “fine” we choose too cut.
You can segment individuals in a variety of ways, but many of these ways may not be useful for the questions you seek to answer. I may be identified as a “mid-twenties jazz music buff,” an “urban chess student and wine lover,” or as someone who “drives American” because I own a Pontiac. These are all accurate segments that connect me with others and offer some snapshots into my interests and purchasing preferences—but is it helpful to you? I feel there is a normal distribution related to the amount of segmentation conducted—a natural sweet spot, after which further division can create more problems than answers, or more incorrect conclusions than accurate ones.
Following the questions of “how do we cut” as well as “how deep” lies the next step: how should we use this information? Does segmentation serve as the sign post for a new fundraising strategy? Or does it simply signal more research? There are successful applications of both I believe, but it depends on the segmentation process and the questions you are trying to answer.
Read this article, consider analytic's emerging seat at the table in our world, and then ask yourself this question:
“How would I want to be identified (segmented) by organizations or causes I care about?”
What’s for Dinner? The pollsters want to know
If there’s butter and white wine in your refrigerator and Fig Newtons in the cookie jar, you’re likely to vote for Hillary Clinton. Prefer olive oil, Bear Naked granola and a latte to go? You probably like Barack Obama, too. And if you’re leaning toward John McCain, it’s all about kicking back with a bourbon and a stuffed crust pizza while you watch the Democrats fight it out next week in Pennsylvania.
Read More
Labels: Analytics concepts, Analytics Implementation, Book Recommendation, General Development and Metrics
posted by Alexander Oftelie at
5/14/2008
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